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投稿时间:2006-09-29 修订日期:2006-11-03
投稿时间:2006-09-29 修订日期:2006-11-03
中文摘要: 从新一代天气雷达径向速度资料中反演出可靠的三维风场对提高新一代天气雷达的应用
水平有重要的作用,将雷达直接观测的径向速度转换成台站预报员更为熟悉的风场结构,对
识别中小尺度信息有很大帮助。为此该文对4DVAR同化技术在风场业务反演中应用的可能性
进行了探讨,利用广州、济南新一代多普勒天气雷达观测资料,从是否加入云模式湿过程以
及迭代次数、计算时间、背景场、初始场、分辨率和反演区域等方面对干模式的4DVAR系统
进行了讨论,并从风场结构、均方根差别等方面对反演结果进行分析。多种试验表明,干模
式的4DVAR系统与湿的云模式反演结果差异不大。模式的初始场和背景场对反演结果具有较
高的敏感性,利用前一时次的反演结果作为背景场迭代15~20次的干模式结果可以很好地在
业务上试运行,对台站预报员提高中小尺度天气预报的准确率有着很重要的作用。
Abstract:It is very effective to improve new generation weather radar application that re
liable 3D wind fields are retrieved from real time radar radial velocities. The
retrieved wind field can help forecaster to identify the mesoscale structures. T
he potential usage of 4DVAR assimulation technique with pure dynamical process t
o retrieve wind field in real time is examined by
using the Doppler radar data in Guangzhou and Jinan. It is argued whether the we
t process needsto be input into cloud model, and what should iteration number,
retrieval area, background and initial fields be, etc. In addition, the retrieva
l results are analyzed from different aspects including wind field structure, co
mputer time, mean square deviation etc.
Tests show that there is little difference between retrieved results from th
e dry and wet 4D VAR systems. Given a background field, the basic characteristi
cs in low level wind fields can be presented from dry model by 15 20 iteration
s, and model results are high sensitive to initial and background fields. Under the
condition of background field, dry results iterated 15 20 times can be effecti
vely operated, which are beneficial to improve the accuracy of meso , micro s
cale weather system forecast.
文章编号: 中图分类号: 文献标志码:
基金项目:国家自然科学基金项目(40375008)、敏视达公司项目“低层风场反演系
统和边界层辐合线风切变识别系统研制”和国家973项目(2004CB418305)
的联合资助
作者 | 单位 |
牟容 | 中国气象科学研究院灾害天气国家重点试验室,北京 100081 |
刘黎平 | 中国气象科学研究院灾害天气国家重点试验室,北京 100081 |
许小永 | 中国气象科学研究院灾害天气国家重点试验室,北京 100081 |
庄薇 | 中国气象科学研究院灾害天气国家重点试验室,北京 100081 |
引用文本:
牟容,刘黎平,许小永,庄薇,2007.四维变分方法反演低层风场能力研究[J].气象,33(1):11-18.
Mu Rong,Liu Liping,Xu Xiaoyong,Zhuang Wei,2007.The Capability Research on Retrieving Low Level Wind field with 4D VAR Assimilation Technique [J].Meteor Mon,33(1):11-18.
牟容,刘黎平,许小永,庄薇,2007.四维变分方法反演低层风场能力研究[J].气象,33(1):11-18.
Mu Rong,Liu Liping,Xu Xiaoyong,Zhuang Wei,2007.The Capability Research on Retrieving Low Level Wind field with 4D VAR Assimilation Technique [J].Meteor Mon,33(1):11-18.